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Shaping the Morphology of Gold Nanoparticles by CO Adsorption
Keith McKenna* and Alex Shluger
London Centre for Nanotechnology17-19 Gordon StreetLondon WC1E 6BTUK
Department of Physics and AstronomyUniversity College LondonGower StreetLondon WC1 0AHUK
modelling the structure of nanoparticles at finite temperature and pressure
* e-mail: [email protected]
Outline
Introduction
Experimental probes of structure and dynamics
1. Atomic scale dynamics
empirical potentials + Monte Carlo
2. Au nanoparticle interacting with CO
DFT + statistical mechanics
3. Atomistic models
multiscale (P,T,N,t)
Summary
Introduction
• Why is the modification of the structure of nanoparticles by molecules interesting?
– because NP properties are very sensitive to their structure
– deliberate
e.g. SAM passivation, molecular electronics, plasmonic waveguides, biological markers...
– environment
e.g. catalysis, gas sensing, nanotoxicology, earth sciences...
Pablo D. Jadzinsky et al, Science 318, 430 (2007)
Artist's impression of a molecular electronics device G. Rupprechter, Annual Reports on the Progress of Chemistry 100 237 (2004)
• Molecule-induced structural transformations
– transformation in average morphology
– atomic scale fluctuations at finite temperatures
– molecules are significant perturbation (large surface/volume ratio)
– properties modified: electronic, chemical, optical, magnetic...
• Theoretical models– state of the art is ab inito:
models often assume rigidity of the NP
– timescale gap (MD)
• Experimental characterization– in situ probes
– difficult to uniquely identify origin of effects
However...
Metallic nanoparticles in atmosphere
• Catalysis– pollution filtering in automobiles and
industry (e.g. CO oxidation)
– CNT growth
• Chemical sensors– modification of electronic or optical
properties
• Molecular electronics– noise, reliability issues
N. Lopez et al., Journal of Catalysis, 223 232 (2004)
S. V. Ryabtsev et al., Semiconductors 35 869 (2001)
Pd/SnO2
Experimental probes
• Scanning probes– STM, AFM...
– topographic and spectroscopic
– in situ rare
• Temperature programmed desorption– adsorbed molecules - coverage and
energy
– ex situ, non-equilibrium
• Photoelectron spectroscopy– direct probe of electronic structure
– indirect probe of morphology
STM - G. Yang et al - Surface Science 589 129 (2005)
Au
TPD - C. Lemire et al, Surface Science 552 27 (2004)
• Transmission electron microscopy– atomic resolution possible
– e.g. Pd NPs on MgO(100) exposed to oxygen and annealed
– interpreted in terms of O modified surface energies (Wulff construction – large particles)
– possible role of electrons (metallic clusters have positive electron affinity)
H. Graoui, S. Giorgio and C.R. Henry, Surface Science 417, 350–360 (1998)B. Pauwels et al., PRB 62(15) (2000)
Pd/MgO
O2 and annealAu/MgO
• X-ray Absorption Fine Structure (XAFS)
– probe local structure (coordination)
– timescale ~ 1-10Hz
– e.g. Pd and cycled CO/NO
– also used in situ IR spectroscopy
– not just oxidation → structural change
M. A. Newton et al, Nature Materials 6 528 (2007)
• IR spectroscopy
– e.g. Au/TiO2 in CO pressures
– appearance of additional IR band on increasing pressure
– persists to low pressure (hysteresis)
– flattening of particle shapeT. Diemant et al, Topics in Catalysis 44, 83 (2007)
It can be very difficult to uniquely interpret what is happening using a single technique
Theoretical models
• What is the favoured nanoparticle structure in vacuum?
– thermodynamic equilibrium
– empirical potentials (Sutton-Chen, TB-SMA...)
– can also include NP-support interactions
– DFT for small clusters (static)
– global minimisation (genetic, simulated annealing...)
– dynamics (MD - small timescales) http://www-wales.ch.cam.ac.uk/CCD.html
many-body attraction
short-range repulsion
• Nanoparticles of different symmetry preferred as a function of size (e.g fcc):
100
111
111
111
111
Icosahedron (strained in bulk)
OctahedronTruncated octahedron
Wulffconstruction
• Compare the energy of clusters with different symmetry
– average excess energy per surface atom
– e.g. Baletto et al, J. Chem. Phys. 116 3856 (2002)
– icosohedral - small N
– truncated octahedral - large N
bulk strain∝ N
Atomic scale dynamics
• Finite temperature– surface diffusion
– kinetic barriers (lower at surface)
– metals (E=0.1-0.6eV) (ms at RT)
– transient configurations
– low probability configurations may be important (t> 103 s)
• Monte Carlo approach– probability to find a given structure
(equilibrium)
– statistical distributions of properties
– average properties of set of configurations from NPT ensemble (P=0)
– surface atom trial move
– embedded atom model potentials
C. L. Cleveland et al, PRL 81 (1998)K. P. McKenna et al, J. Phys. Chem. C Lett. 111, 2823-2826 (2007)K. P. McKenna et al, J. Chem. Phys. 126, 154704 (2007)
Free Au nanoparticle
• Effect of temperature structure (P=0)– Au NP with 1152 atoms (size ~3nm)– magic number truncated octahedron– full exploration of configurational space
• Results
K. P. McKenna et al, J. Chem. Phys. 126, 154704 (2007)
Typical room temperature morphologyIncreasing concentration of low coordinated atoms with temperature (3C)
Roughening transition associated with (111) facets
surface melting may occur at lower T than roughening
phase transition
Size of (111) facets
Energy
Au NP supported on MgO(100) surface
• The system:– 1-2nm diameter
– Au binds to O preferentially
– 3% lattice mismatch
– Epitaxial structure
– N=181 - 191
– T=250K - 800K
B. Pauwels et al, PRB 62 (2000)K. P. McKenna et al, J. Phys. Chem. C Lett. 111, 2823-2826 (2007)
Expectation energyDiscontinuity in configurational contribution to specific heatSmall compared to vibrational and electronic contributionsSecond order phase transition
9C sitesCorrespond to ideal Au(111) facetsAlmost independent of temperature below 500KRapid decrease in size of ideal facets after 500KPhase transition is associated with roughening of the (111) facets
Au-MgO Interface layer8C sites in the interface layer are fully coordinatedProbability distribution indicate magic numbers nmAbove 500K also get appreciable non-magic numbersDisordered interface layer
7C interface layer sites correspond to the perimeter sitesThe number of these decreases sharply after 500K
Therefore the roughening transition is a complex one involving Au(111) facets and the perimeter of the Au-MgO interface layer
4C
3C
Increasing concentration of low coordinated atoms with temperature (3C)
Effects of pressure: CO and Au NPs
• Molecules– adsorb and desorb from the NP
– may also react - catalysis
– can change NP morphology
• Thermodynamic equilibrium– equilibrium of molecular
adsorption/desorption
– equilibrium of NP configuration
– very large configuration space to investigate
• Constrained equilibrium– consider various possible
structures
– for each look at equilibrium with ambient
– configuration with lowest Gibbs' free energy of adsorption is favoured
),(),()(),( TPTPNNGTPG gasadsadsads
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iads ETPfN
statistical mechanics: equate chemical potentials of gas and adsorbed phase
K. P. McKenna et al, J. Phys. Chem. C Lett. 111 18848 (2007)
• CO on an Au nanoparticle– NP active for CO → CO2
– CO adsorbs in the top position
– increased adsorption for low coordinated sites (cluster study)
N. Lopez et al., Journal of Catalysis, 223 232 (2004)
L. M. Molina and B. Hammer 69 155424 (2004)
CO→CO2 (Au/MgO(100))
• 79 atom Au neutral cluster– agreement on truncated octahedron structure for
many different empirical models (SC, EAM, etc)– optimise using DFT
– GGA PAW method (VASP)– 400 eV cut off– 21Å3 cubic cell
• DFT provides:– energy of NP configurations (without molecules)
– diffusion barriers between configurations
– adsorption energy for molecules on different sites, i
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Alternative NP configurations
3C
3C 4C
4C
CO adsorption
– overestimation by DFT but trends reliable
– adsorption energies increase with decreasing coordination
– always Au-C-O
– localised relaxation of Au NP
– correlation with Ecomd
– 3/4C - similar adsorption energies (both adatoms on (111) and (100) surfaces
IR spectra
• Bonding transition– physisorption to chemisorption
Z < 7
– Au-C bond length changes
– Au-C vibrational mode calculated by finite differences
– two distinct bands
– provides a measure of relative population of sites
• CO stretching mode– 2060-2170cm-1
– less distinct bands
Ab inito thermodynamics
• Average coverage of CO– NP with low coordinated sites
gain energy compared to more truncated structures
– balance of reorganisation energy and adsorption energy
• Proposed configuration change– exposes 4C Au atoms while remaining truncated
– tendency towards octahedral
– which configurations are favoured at different T and P
Atomistic models
• Why atomistic?– DFT calculations expensive
– consider dependence on N for different systems (multiscale)
– DFT to parameterise atomistic models
• Energetics– lattice model based on TB-SMA
+ 2% Ecoh strain for Ico
ZEads
Z
ZEE
• Compare Icosahedral, octahedral and truncated octahedral
– can analytically determine Nz for different symmetry types
– directly related to XAFS
e.g. D. Glasner and A. Frenkel, XAFS13 processings
Mean Z higher but at the expense of bulk strain
• Compare energy of different clusters:– first in vacuum
– simple model is qualitatively reasonable
– icosahedral → truncated octahedral
Ico
Octa
TO
• Dependence on pressure and temperature for Au– icosahedral → octahedral → truncated octahedral
Octa
Ico
TO
Pd
Ag
IcoTOOcta
Phase diagrams
Au
Al
17,000
33,000
24,000
30,000
20-200 atoms (1-2 nm)
5 decades of pressure
Summary
• Structural trends modified by molecules at finite P and T
• Even low pressure can be different to vacuum
• Influences properties: optical, electronic, chemical...
• Transformations depends upon:– composition of NP
– adsorption properties of molecules
– interactions with substrate
• Connect to measurable properties– XAFS (rdfs)
– electronic structure - spectroscopies
– optical properties - plasmon spectra
– topographical probes
– IR, TPD, ...
• Future developments– non-equilibrium dynamics by kinetic MC simulations
– effect of substrates, interactions between nanoparticles (grand canonical)
– combine theory and experiment to understand transformations
Acknowledgements
This work funded by the EPSRC Materials Modelling Initiative grant GR/S8000/01.
Computational time on HPCx provided by the Materials Chemistry Consortium through EPSRC grant EP/D504872/1 and on C3 through UCL research computing.
Thanks to the following people for useful discussions:Peter Sushko, John Harding, Oliver Diwald, John Venables & Marshall Stoneham.